In several key respects, COVID-19 reveals how crucial timing is for human life. The lens of complex systems science helps us understand the central role of time in coordinating across scales, and how synchrony or misalignment leads to major consequences—whether it’s in how the metabolic differences between bats and humans can create an opportunity for interspecies epidemics, or in how the timing of society’s return to work could either help reboot or help destroy the world economy. Network research shows us early warning signs of an impending social crisis, the fossils of a vast collective computation as we struggle to adapt to periods of rapid change…and even the analogies we use to talk about these times bely a nested and embodied structure in how we encode the details of reality. These are complex times, indeed—and how civilization mutates to adapt to this pandemic will have everything to do with our ability to think and act at multiple timescales, simultaneously.
In Transmission, SFI’s new essay series on COVID-19, our community of scientists shares a myriad of complex systems insights on this unprecedented situation. This special supplementary mini-series with SFI President David Krakauer finds the links between these articles—on everything from evolutionary theory to economics, epistemology to epidemiology—to trace the patterns of a deeper order that, until this year, was largely hidden in plain sight.
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Further Reading:
005: Andrew Dobson on the Need for Disease Models which Capture Key Complexities of Transmission
006: Miguel Fuentes on Using Social Media Data to Detect Signatures of Global Crises
008: Michael Hochberg on the Importance of Timing in Restrictive Confinement
009: Melanie Mitchell on How the Analogies We Live by Shape our Thoughts
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Michael
David, it's a pleasure to jump back into the complexity with you.
David
Yes, I'm looking forward to summarizing the next five Transmissions.
Michael
And it's a good five this week. We've got Andy Dobson… Let's start there on Andy Dobson's “Need for disease models which capture key complexities of transmission,” because the origin story of this novel coronavirus in another animal is a really interesting point of the way that this is going to be remembered and a really key entry point for understanding some of the systems dynamics that have been revealed to us more popularly through this crisis.
David
Yeah, so Andy's was a very rich contribution, I felt, and he made three very deep points. The first point was, why is it that a disease like this one is so much worse in cities, whereas a disease like malaria is actually worse in rural communities? And it comes down to this technical insight of what the modelers call a “density-dependent transmission” versus a “frequency-dependent transmission.” With density dependence as the term would seem to imply, the higher the density, the more transmission there is. And that's why we're socially isolating. So the more people there are as there are in cities, the more the virus can spread. But if you look at a vector-borne diseases like malaria, it's quite different. When the mosquito takes a blood meal that transmits this protozoan parasite, the malarial parasite, it has to stop and digest. And so if you present to the mosquito another potential susceptible host, there's nothing it can do because it's busy digesting. And so as you increase the number, the density, if you like, the number of people, that doesn't necessarily increase the transmissibility. And in fact as the population grows, the relative rate of transmission goes down. And so they thought that was a very interesting point to make because people might be wondering why it is that not all transmissible diseases are worse in urban centers or high-density.
So that was his first point. The second point I thought was really cool and had to do with, if you like, the biomechanics of flying mammals, in this case bats. So bats, like all flying mammals, have to have particularly light bones. And a consequence of that is that there's less of a volume of bone marrow, and bone marrow is where B cells of the immune system are synthesized. And the B cells create antibodies that create the inflammation that creates the pathology. And so bats, by virtue of being volant mammals, flying mammals, are actually in some sense, naturally more resistant to immune pathology. So that was a really interesting point. He then went on to make another point about bats, which was every time a bat flies, in some sense it's generating a mini fever. And high body temperature, as everyone knows, is one way that physiology has invented to rid ourselves of infection.
So the bat is in some sense generating this fever every time it flies and killing off any viruses or some number that it might be infected with. And the third thing about bats is that they enter into what's called torpor. And torpor is a little mini hibernation where they have very reduced activity and that naturally socially isolates the bat. So in its natural repertoire of behaviors, it has built into it in some sense a natural means of combating viral infection that we do not. And that goes some way to explaining why bats don't suffer as much as humans.
Now, Andy's final point is actually the most technical and most frightening. Every species that gets infected with a virus has a natural epidemic cycle. And the factors that contribute to that cycle are things like how long they live, how quickly they reproduce, and so forth. And small mammals reproduce more quickly and have shorter lifespans, and large mammals conversely reproduce slowly and have longer lifespans. And that means our epidemic cycles are slow relative to a bat.
Now as long as we have separate, largely uncoupled life histories, that's fine. But now if you increase the transmission between species to a level that you would observe within the species, something very alarming happens, and that is that the faster epidemic cycle dominates the slower one—which means that the bat species could drive the human species extinct, because we would be living in some sense on the timescale of a bat population. So in this case we kind of dodged a bullet because even though it's dreadful, there was in some sense one or a few points of contact, but if human beings persist in the stupidity of engaging at a high rate, through whatever means of transmission, with nonhuman species such as the bat population, then there's a real prospect of a far worse entangling of the epidemic cycles potentially leading to a very significant reduction in the human population.
Michael
Yeah, this is an interesting place to enter the question of what you brought up last week, in terms of intentionally misaligning phenomena occurring at different scales, uncoupling systems that are operating at different scales, and this I think also touches on Rajiv’s paper. We'll discuss later, as you know, we’re looking at the epidemic timescale in bats, the epidemic timescale in humans, but then also the way that this epidemic is rippling through our economic systems and so on. There are a lot of areas where we either want to drive them apart or we are forced to align timescales to shift our economy in order to make it sort of work with the human epidemic timescale. But that's getting ahead of ourselves.
David
Well, no, I think it's a really important point you make as, as I'm not sure everyone understands or knows, SFI has been for a long time fascinated with this topic of “complex time,” which is how temporal phenomena play out across the scales of the complexity of the earth. And what evolution has done is it's created this interesting coupling of all of these clocks. You can think of every species as being a little clock that ticks away at its own rate and we interact at some level, but we're not strongly coupled. And if we strongly couple, then you get these strange synchronizations that appear. And in this case, the synchronization is dominated by the fastest clock. And in the case of transmission, that could be a lethal synchronization.
Michael
So to get back to the core of this series and the dynamics of transmission. Let's talk about Michael Hochberg’s piece.
David
Yeah. Michael is in some sense is doing what John did last week in presenting us with the intuitions of a simple model. And the intuition that he's trying to instill, which we have a very hard time with, is exponential thinking. Human beings are basically by default linear thinkers. You double the size of that, you double the effect, you know. It takes twice as long, you know, and it's twice the effort. But in the exponential regime, that's not true. These nonlinearities dominate. And the one that Michael focuses on is again, this enigmatic quantity that everyone is talking about, but in England we call “R naught.” But here we call “R sub zero,” which is the number of new infections caused by a primary infection. So if I were infected, how many other people I would infect. And we know that for this particular virus, that value is about 2.5 so a primary infection would cause about 2.5 secondaries, which leads to a doubling of the virus about every three days.
What that means in large populations is really kind of staggering and it bears on this whole question that we discussed on coming out of quarantine. So if the initial size, if you like, of the infected population is in the hundreds, in a population of millions as we live in, then thousands of people will be infected. But if the initial population of infected is in the hundreds of thousands, then the total number afflicted will be in the millions. And so this gets back to this crucial insight that because of the nonlinearity and this doubling effect, as we come out of isolation, it's crucial that we don't expose the world to a very large number of what might be non-symptomatic infected, because we're going to get these nonlinear effects, which lead to millions of people becoming infected.
Michael
Yeah. There's another number here, the the effective reproduction number R(t). I've been hearing people confuse these two numbers. I think it's important to differentiate. This is what you're talking about is the R naught gives you the transmissibility on day zero, but when we're actually looking at how it lands in these different populations, it's not just the size as as we talked about with Laurent Hébert-Dufresne different on an earlier episode. It's not just the size, it's also the structure, but let's set that aside for a moment and talk a little bit about how R(t) is different from R naught.
David
Yeah. The difference is essentially they're very similar concepts, but R naught, as you said, is in a way the concept that we worry about at t=0 when the infection starts, but while the infection is moving along, there's also a reproductive rate of the virus, that's time-variant as the epidemic proceeds. So it's not necessarily just what happens at the beginning that we should be concerned about, but what's happening as the infection unfolds. But they are to all intensive purposes, very similar because they all reflect this effect of the instantaneous current population size on the future epidemic size.
Michael
Yeah. It seems like one key point to take away from that, though, is that when people hear other people talking about lowering the R value for this virus, they're not talking about actually changing the virus itself to become less transmissible. You're talking about network dynamics.
David
Exactly. That’s absolutely right. They all play into that calculation of of R zero or R, and as we said last week, there's been so much emphasis on the molecular biology that we've forgotten that the social distancing measures are an essential parameter in the epidemic modeling.
Michael
So a little bit later this week, we have a conversation with Caroline Buckee coming out, and she's published quite a bit recently on disease surveillance using modern techniques. You know, this is a modern pandemic and so it's a pandemic happening in a world of data surveillance, happening at multiple different scales, and there are a lot of really interesting both technical and ethical questions that come up from that. But one of the reasons that it's such a hot topic is because it would allow us to potentially detect these things a lot earlier than we did this time. Or to be able to respond to them in a much more precise and granular way. So that that brings us to Miguel Fuentes’ piece on “The use of social media data to detect signatures of global crises.” What'd you think about this one?
David
Yeah, this was very interesting and it had that really spooky epigraph from HP Lovecraft, right? Which is, “The oldest and strongest emotion of mankind is fear, and the oldest and strongest kind of fear is fear of the unknown.”
Michael
Which speaks to last week's entire conversation on rigorous uncertainty.
David
It absolutely does. And our desire to do anything in our power to pretend that the unknown is not unknown. What their contribution is, what they've been doing in fact for the last several years, is studying social unrest in their own home nation of Chile. And the question that they ask themselves is, what is the signature of social crisis? And they're interested in that largely because they want to detect it before it unfolds. And they've been studying social media, in particular tweets and Twitter feeds, and they made an interesting discovery. In retrospect I think it's pretty obvious, but I think it might not have been before the analysis was performed. And that is, during periods of high crisis—that is during marches, during demonstration, during periods of significant civil unrest—if you look at the social graph, if you like, or the social network that you can reconstruct from tweets who sends messages to whom and so forth, you observe that during crisis, that graph has a very particular top logical structure. And that structure is that messages are very clique-ish and they center around a very small number of dominant themes, dominant terms of course, or keywords or tags. And so the graph kind of fragments and the particular reach of any particular person in that social media graph is limited. As you move into periods of low crisis, the number of terms or tags becomes more diverse and its reach increases. It extends over longer distances in the graph. And what was intriguing, I think, about their analysis of this particular dataset in Chile during the civil unrest, is that those signatures were present before people were out in the streets.
It gets to our point last week, right?: that technology allows for mimetic transmission to be in advance of behavioral and biological transmission, and in just the way that we fail to act with alacrity in the presence of the data which we discovered today, for example, with much earlier maps, perhaps even in January, we knew this…that there are similar questions about social unrest and it and it raises, you know it's a double-edged sword. On the one hand, yes, you might be able to see this. On the other hand, in whose hands is that appropriate information and how would we use it responsibly?
Michael
Indeed. You know, something that I get out of this—and I'm curious to know your reflections on this—is this sounds a lot like the way that Francesco Varela described the 1973 Chilean revolution, when he spoke of turning on the radio and one radio station would say that it's sunny outside and another radio station would say it was raining. It was like a fragmentation of reality. And you know, there's, there's been a lot of research at SFI, including work by Joshua Garland, on polarization of networks on social media. Reading Fuentes’ piece, it almost reminds me of the meiotic spindle and the polarization of chromosomal pairs at the moment that we're seeing this transition—a cell’s reproductive cycle. Without suggesting that there's any kind of developmental telos here, I’m curious in relation to your earlier remarks on multiple different timescales and the way that an epidemic in a smaller organism can drive disease dynamics in a larger organism, whether you think that what Fuentes and his colleagues are observing is the network coupling two phenomena that are going on at different scales, at different paces, and attempting to adapt to accommodate that.
David
Yeah, I think you're right that what's happening is, of course, we're all now obsessed over this virus and it's rather dangerous actually. We’re becoming a memetic monoculture, the news that should be reaching us is not, and our cliqueishness with respect to ideas is shrinking and I think it's a good example of that phenomenon. What’s surprising, I think when one performs these analyses of the kind that Miguel has, and Josh and others, is that what is clear at the level of our social lives also manifests at the population level, the national level. And that's surprising. I think it's very difficult for us to project out our own psychological insights into the collective—and what the social media data is allowing us to see is these echoes, if you like, of the micro in the macro. And it needed to be that way. But in this case it does seem to be the case that as we become, in some sense, more narrow in our obsessions, so does culture at large.
Michael
To explore this a little bit further, I just read a really fascinating essay about the Thirty Years’ War: the Anabaptists holing up in Munster fighting the Catholic Church, and the way that the fragmentation of Christianity across Europe was driven by the circulation of pamphlets due to the recently invented printing press and the way that, this was an early modern information explosion that led to a phenomenon that Fuentes would call a “crisis,” in the way that you know it bears this kind of signature in its networks. We talked a lot in the first episode about the way that the social contagion dimensions lay over this and make this, again, like a distinctly information-age pandemic. That period in the 16th century, 17th centuries… We’re going to talk about Melanie Mitchell's work on analogies here in a little bit, and I'm curious to what degree you might find that particular period of polarization and loss of collective narrative coherence as a useful analogy or guide for what's going on now—and then moving into Rajiv's piece with Danielle and Glen, what does that suggest in terms of our options for recovery?
David
Yeah. So if we look at the article by Rajiv, Glen, and Danielle, what this is saying at the broadest level is that we have to be equally as sophisticated in the treatment of the socioeconomic networks as we are coming to be in the treatment of the social epidemiological networks. And again, it gets to last week—we’re so accustomed to these reductionist forms of thought where we look for these magic bullets at the genetic level, that we've become blinded to the fact that they're by and large useless at the level of the collective, and we need new insights, which is in part what complexity tries to do. What they are proposing in their article is something in some sense, in retrospect, very obvious—which is that we need a multiple timescale approach to this crisis that makes most effective use of confinement testing and mobilization. And they call their strategy “mobilize-to-transition.”
The basic concept of mobilize-to-transition is while we are in confinement is the time when we should be maximizing virological and serological testing in order to move the either resistant or immune subset of the population back into the economy. So we don't wait for the wave of the pandemic to subside. You actually are actively mobilizing now while in confinement. And the point that they make, which I think is the most important, has to do with this question of technological certification—because everyone's asking this question: “If I tested negative and I returned into work, well how do you know that I haven't been infected the meantime? Right? Because I've been exposed to any number of people by coming back to work and we can't be absolutely sure everyone is still negative.” Now with serological testing, with antibodies, we're more secure because we hope you have persistent immunity and that's where technology comes in.
And so they are suggesting we need to develop new technologies, which certify negative-tested or serological positives that are reliable and can be accessed by other individuals. So it’s as if, Michael, we both came into a room and I looked at my phone and it said, “Yes, you can talk to Michael because he's a safe contact,” but you can again note how frightening that might be with respect to security. So I think the bigger question that they're raising is, yes, we need the sophisticated schedule of social change. We need a technological means of certification and we need to be sophisticated about the robustness of that certification.
Michael
There's another piece here which ties into—if people heard Rajiv's episode of this podcast when he was here talking about stereotyping and criminal justice, and he was talking about the imbalanced distribution of stop and search that certain groups are targeted due to ethnicity for discriminatory police action. And he uses that as an interesting metaphor here, to explain what we want to tune this process of testing for, in terms of optimizing for a best distribution of testing. Why don’t you talk about that a little bit?
David
Well, now, this just gets to this point again, it's very general. I'm not sure we have a good answer to this. Which is what you don't want, right? Is all of these biases built into your process because you think you know who the highest-risk individuals are. So in some sense you have to spread your survey much wider than your prior beliefs might lead you to. And my take away from Rajiv's point on that is that we have to be extremely aware of how we use historical bias to inform future survey, and that the best thing we could possibly do is know it in order to adopt a more uniform sampling strategy.
Michael
Yeah. He says, “If a location is turning up more positives than another at the margin, resources would be better used by shifting to the former at the expense of the latter.” So this is about reallocation of testing through a dynamic process that's provisional and under constant revision. You know, something else that came up around this paper on Twitter is people's discomfort around the idea. Nowhere in this paper does it say that people will be forcibly reallocated into different labor sectors. But of course when you're operating on a fraction of the workforce and there's been a massive shift in the composition of goods and services in economic demand, then it's clear that reallocation is going to happen, but it's going to happen, as they make clear in this, among those who are willing and able. And so this is another piece that I'd like to hear you speak to, which is how this kind of process is going to emerge naturally, rather than being forced in a kind of top down way. That you can't do that with a system like this.
David
Yeah, but this gets to David Kinney's contribution of last week having to do with the limitations of scientists’ insight into policy advice, which is that what Rajiv is saying—very correctly—is there are statistical anomalies that come from these biased samples, and that there are techniques to actively avoid them. In his case, do the inverse, which is one way to do it. But then it leads to your question, which is a policy question, which is how do we then use that kind of insight?
And I have to say, I mean it's one of those cases where it's certainly above my pay grade. I would say it would be my job and the job of our community to be as rigorous as we can with the limitations of the survey and suggesting improvements to harvesting the true information. At that point, we really have to turn to democratically elected officials to make difficult decisions, and to the citizens of the country who elect them. So I'm always very careful about stepping into that domain because I wasn't elected for my sociopolitical wisdom. I was elected for my scientific capability.
Michael
That is a fair caution. What it seems like though is that there is a scientific opportunity here to investigate how the timescale at which people can be retrained suits the timescale at which people are going to be reentering the workforce, and gives us some insight… You know, like when, Maria del-Rio Chanona, Doyne Farmers’ PhD student, came out for the symposium last year and was discussing looking at networks of skills rather than at job descriptions and looking at how we might be able to help people see this in a fresh way by unbundling all of the different capacities that people have. Now that kind of work seems like it would be really useful in advising policymakers on recommendations for retraining and that kind of thing.
David
Yeah, I do think that one thing we've learned in pedagogy is how vastly more flexible human minds are than we thought. And all of us when motivated have an extraordinary latent capability to learn. And so on that side of the equation, I think yes, but you know, as you are, I'm extraordinarily concerned about despotic moves during periods of crisis. They're very hard to undo. And so I would be extremely cautious in giving individuals in political power that instrument to dictate what people should be doing with their lives.
Michael
To the point on plasticity and people being able to change the way that we think about something, that leads us very gracefully into Melanie Mitchell's piece on analogy.
David
Yeah. So this was really a wonderful, thoughtful and very witty contribution having to do with how we struggle to conceptualize a moment like this, and how we're forced to reach for analogies to make sense of it because it seems so unprecedented. And of course Melanie had worked on artificial intelligence systems with Doug Hofstadter to try and draw analogies. So she has a really interesting background in this topic. The first analogy that Melanie mentioned. to flu. And many people and many of us actually were quite confused by the situation because flu, as most people know, infects hundreds of thousands of us citizens a year. That leads to tens of thousands of deaths. Why is it that the coronavirus had a much stronger systemic effect than the flu virus? And one obvious answer to that is, because we knew the flu virus and and society doesn't like uncertainty, as we have established. Just the novelty alone was enough to lead to a strong reaction.
But more importantly, other details of its biology that the coronavirus is more virulent, it's more transmissible. And that means that the rate at which society is being perturbed is higher. And this led to one interesting and amusing quote from someone with a comedic capability, in her article, who said facetiously, “I do not understand how McDonald's can serve 2 billion hamburgers every year, but when I order 5 million at the drive through, it overwhelms the system.” Right? So it's a very important point made there. And is the difference between number and number over time, right? And rate. And the problem, the difference between flu, if you like, and coronavirus is not the number. The problem is the rate.
And she then goes on to talk about these other analogies that we draw, you know that we're in the throws of a tsunami. This is a wave that hasn't crested yet. And the question is what's behind that analogy? And I think what's behind that one is our awareness of something with immense power that we're not aware of until it's too late. That is, in a sense, if you unpack what is meant by a tsunami, that's what's meant—in contrast to a quote that she has from The New York Times where someone says it's like asking a fireman when you can move back into your house, but your house is still on fire. And that's completely different, right? Because that's an inadequate grasp of the risks of a common event. And what that analogy is saying is, “Get real.”
She goes on to develop all of these analogies. And the one that's in some sense, most alarming in reference to our earlier conversation, is the analogy to war. That the pandemic is our war, the war of our time, perhaps World War Three, and with leaders, including presidents and prime ministers referring to themselves as wartime leaders, as wartime presidents. What is behind that analogy? Well, on the one hand it’s a positive that we all have to cooperate. We all have to work together to solve this. We all have to make sacrifices. But there's also a very significant negative. And that is that during a war there is a reduction in civil liberties, and the question we're asking ourselves is, during this so-called war, are we cooperating or are we being controlled? And that's the question when we should ask. So the analogy is not benign, right? It carries with it both positives and negatives and Melanie's deep point is, we should all be very thoughtful about both of those, because they're going to change our behavior in the long run.
Michael
There's an entry through this article to a deeper and broader topic in complex systems thinking generally, which is that these analogies are informal verbal models. You know, SFI External Professor Scott E. Page and his book The Model Thinker. It seems like a kind of adaptation to the information explosion that we were talking about earlier in this call. To try and sort of fortify that an analogy with the printing press, you know this was something that gave people the capacity for peer review. It was a technological innovation that enabled modern science, by a lot of historical accounts, and in some way that's sort of the press was the cause of and solution to the information crisis. So in this sense, at risk of going on a digression I'll have to cut out later…
David
I can answer actually.
Michael
Yeah!
David
I think you make a really important point, which is that in some sense, what we do when we build mathematical models or models of any kind is make analogies. If you look at the early theories of the solar system and the cosmos, they were based on clocks, right? In other words, mechanical devices, we used to model the motions of the planets, and so hence we have our armillary spheres and astrolabes and all of these extraordinary devices that are in some sense embodied physical analogies. And you're right, say that we should understand that because what your brain is doing when someone says this is like a tsunami, is you are in some folkloric sense invoking fluid dynamics. You're saying, “I know what a wave is. I know how they're propagated. I have an understanding of the force behind them. I understand what happens when they reach shallow ground and a wave breaks.” So you have in your mind a mechanical picture of a dynamical system. It's just that you are not writing it down rigorously in mathematical terms. But your brain is using a similar understanding of mechanics, and it's a very natural extension in fact from the verbal analogy to the mathematical model. So it's actually one of the very powerful things that the brain does, and it allows us to arrive at insights without doing a considerable amount of formal work.
Michael
The question that Melanie's calling us to hear I think is really important, which is, not all models are created equal. There may be moments where the complexity of the situation calls for a kind of holding together of multiple models to get a stereoscopic view, to see things knowing that each model is hiding crucial aspects of the situation, and suggesting things that we don't want, like you mentioned, you know, the wartime footing tends to lead to xenophobia and so on. So these are different stories in a sense that are inhabiting a kind of evolutionary landscape. And some of these models are really robust and ancient, and some aren't. And in communicating them, some of them are simple enough to be effectively communicated, but like we were talking about in the last episode, the most encompassing complete model may be dependent on data that we don't have or may overfit a rapidly changing situation. So I think this really speaks to the issue of careful science communication, here.
David
Well yeah, again, this analogy concept and the relationship to models is very deep. I mean we could all sit down, it might be an interesting exercise in fact, and say, okay, let's take the three analogies that are in play here, “war,” “tsunami,” and “fire.” And if you were to sit down and just write down a list of what those things implied and which one we thought was the best fit to our circumstance, it's quite interesting. Right? War typically has relatively equally matched adversaries who have strategic interests that are being in some sense reached for through conflict, typically territorial expansion. Does that fit this circumstance or not? And I think it's a very interesting exercise, because language is so seductive and so infectious, and sentences are so easy to repeat, we often forget that they carry specific meanings. I think that Melanie's contribution is asking us to consider what those meanings really are.
Michael
Indeed. Well that's a fine place to wrap it for this one, unless you have…
David
No, I think that's really great. I thought I might mention briefly what we're going to be dealing with next week.
Michael
Let's do it.
David
So just again, another batch of five really interesting thoughtful pieces. We will have a contribution on investment. What is the right thing to do in a market such as this? And of course Bill Miller will be making that contribution, our former Chairman of the Board and obviously a very well known investor. And of course Bill is always extraordinarily brave and says now is the time to take risks. We’ll have contributions from virologists in Spain who are on the front line of repurposing basic science virus labs to create PCR-based tests, all the way through to paleontologists like Doug Erwin, who is going to be discussing what we can learn from the history of mass extinctions in the fossil record and their recoveries.
Michael
Doug's always great for the gallows humor that you can only get from a paleontologist who studies mass extinctions.
David
Everything pales in comparison to their dataset!
Michael
Yeah! It’s also worth mentioning, I think that the InterPlanetary Festival, which has unfortunately but understandably been canceled, has been working on a series of online course materials around this essay series and this podcast. And you can go and sign up for weekly PDFs with all kinds of fun supplementary material at interplanetaryfest.org. It’s been lovely, when we're talking about the spontaneous and self-organizing reallocation of labor, it’s been great to see that team pumping out these materials. They're really, really good.
David
Yeah, they're great. And I would just suggest, for those of you who have kids or are looking for something to discuss in confinement with your families and going a little stir crazy, what this does, and I think the InterPlanetary team done a great job, is it takes a lot of these Transmissions, renders them in a more accessible language, and couples them to quizzes so that you can all discuss some of these topics and do something hopefully constructive rather than all losing your minds.
Michael
Learning it multiple scales at once. All right, David, it's a pleasure. Looking forward to catching up with you on the next set next week. Fantastic.
David
Thank you, Michael. Thanks everyone. Be safe.